Method and system for generating and displaying function call tracker charts

ABSTRACT

A method for generating and displaying function call tracker charts is disclosed. In one embodiment, the method includes importing trace data at a database from a provider, tracking a plurality of factors associated with the trace data, and generating a first graph to represent each of the plurality of factors associated with the trace data.

FIELD

Embodiments of the invention generally relate to the field of tracing. More particularly, the embodiments of the invention relate to generating and displaying function call tracker charts.

BACKGROUND

As application development projects are growing larger, tracing is becoming increasingly important. Tracing can be a very useful tool used primarily by software developers to isolate problems, for example, by tracking execution of program code. For example, when developing an application, developers trace the execution of methods or functions within certain modules to identify problems and/or to determine if the program code may be improved. If a particular method takes an inordinate amount of time to complete, the developer may determine the reasons why and/or change the program code to operate more efficiently.

Trace tools are proprietary application programs which use different techniques to trace the execution flows for an executing program. One technique, referred to as event-based profiling, tracks particular sequences of instructions by recording application-generated events as they occur. By way of example, a trace tool may record each entry into, and each exit from, a module, subroutine, function, method, or system component within a trace file (e.g., a time-stamped entry may be recorded within the trace file for each such event). Trace events may also be sent to a console or other output destination.

Conventional trace tools, however, are limited with tracing data from various systems, i.e., when dealing with tracing data of various structures. For example, conventional trace tools do not provide for integration of various trace files of different structures relating to different corresponding systems. This often leads to, at best, delay in reading of errors as the data has to be manually read and, at worst, misreading of errors or even loss of trace data. Tracing is particularly cumbersome when a development project involves a great number of systems, applications, components, modules, developers, and/or multiple interfaces and services. Furthermore, conventional trace tools are limited in the way they display tracing information.

SUMMARY

According to one embodiment, a method for generating and displaying function call tracker charts is disclosed. The method includes importing trace data at a database from a provider, tracking a plurality of factors associated with the trace data, and generating a first graph to represent each of the plurality of factors associated with the trace data.

Other embodiments are also disclosed. Further, the above attributes may be implemented using a computer program, a system, or an apparatus, or any combination thereof. These and other details of one or more embodiments of the present invention are set forth in the accompanying drawings and in the description below.

BRIEF DESCRIPTION OF THE DRAWINGS

The invention is illustrated by way of example and not by way of limitation in the figures of the accompanying drawings in which like references indicate similar elements. It should be noted that references to “an” or “one” embodiment in this disclosure are not necessarily to the same embodiment, and such references mean at least one.

FIG. 1 illustrates an embodiment of a common performance trace architecture.

FIG. 2A illustrates an embodiment of a common performance test application programming interface.

FIG. 2B illustrates an embodiment of a mechanism for using a common performance test application programming interface.

FIG. 3 illustrates an embodiment of a common performance trace architecture having a central administration system.

FIG. 4 illustrates an embodiment of a process for tracing and importing trace data.

FIG. 5 illustrates an embodiment of a trace data structure represented at a common performance trace database.

FIG. 6 illustrates an embodiment of a process for tracing at multiple systems and providing access to trace data.

FIG. 7A illustrates an embodiment of a common performance trace architecture having a central administration system.

FIG. 7B illustrates an embodiment of a central administration system.

FIGS. 8A-8B illustrate embodiments of chart representation graphs of function calls.

FIGS. 9A-9B illustrate embodiments of chart representation graphs of data aggregates of function calls.

FIG. 10 illustrates an embodiment of a process for creating and displaying trace data.

FIG. 11 illustrates an embodiment of a process for importing and displaying trace data.

FIG. 12 illustrates a computing system.

FIG. 13 illustrates a client/server network system.

DETAILED DESCRIPTION

As used herein, references to one or more “embodiments” are understood as describing a particular feature, structure, or characteristic included in at least one implementation of the invention. Thus, phrases such as “in one embodiment” or “in an alternate embodiment” appearing herein describe various embodiments and implementations of the invention, and do not necessarily all refer to the same embodiment. However, they are also not necessarily mutually exclusive. Descriptions of certain details and implementations follow, including a description of the figures, which may depict some or all of the embodiments described below, as well as discussing other potential embodiments or implementations of the inventive concepts presented herein.

FIG. 1 illustrates an embodiment of a common performance trace (CPT) architecture 100. In one embodiment, central administration system (CAS) 104 is employed coupled with monitored systems 122, 136, 146, such as a Java 2 Enterprise Edition (J2EE) system 122, an Advanced Business Application Programming (ABAP) system 136, and a third party system 146 via various application programming interfaces (APIs) 152-156. The trace data is retrieved from the remote systems using various APIs and transport protocols (like HTTP, RFC). It is contemplated that any number and type of monitored systems may be coupled with CAS 104. CAS 104 receives trace data from various monitored systems 122, 136, 146 and collectively provides the trace data in a common structure or format (e.g., CPT format) at database 120. Having a common structure or format for trace data allows the user to choose the data provider or monitored system 122, 136, 146 that meets the requirements or needs in light of changes to one or more applications, program codes, etc. A CPT format includes a format for common performance trace events that unifies different types, structures, and formats of performance data, such as the ones obtained from a structure query language (SQL) trace, a J2EE server performance trace (e.g., from a J2EE system 122, a ABAP server performance trace (e.g., from an ABAP system 136), and the like (e.g., from a third party system 146).

In one embodiment, CPT architecture 100 provides a mechanism for persisting and analyzing performance traces from various monitored systems 122, 136, 146. A performance trace refers to a special trace type that deals with performance issues of applications and program codes, such as like call durations, call stacks, memory consumption, amount of transferred data, and the like. CPT architecture 100 may consist of common data format, trace data providers, central analysis services, generic reports, and the like. CPT architecture 100 further provides a library that provides one or more APIs (e.g., CPT API) to give access to CPT files and database 120. A CPT API refers to an interface that allows for generation and persistence of performance trace data, which complies with the CPT format that is provided via CAS 104 and stored at CPT database 120, and manages various CPT processes as discussed elsewhere in this document. In one embodiment, a trace correlator is employed at CAS 104. A trace correlator includes an object that is used to analyze trace records, which are obtained from different, software components, physical locations (e.g., hosts) and at different times. A trace correlator helps define a semantic group, which is useful to understand how various traces belong together. Also, distributed statistics may be used that refer to a minimum performance trace, which continuously runs with a running system, such as monitored systems 122, 136, 146. It may be aggregated offline to statistical aggregates and analyzed with respect to performance, accounting, hardware sizing, system usage profiles, and the like.

CAS 104 is in communication with client 102. CAS 104 includes Mbean server 105 that is registered with CAS 104. Further, display application or user interface (UI) 106 (e.g., WebDynPro Runtime) is employed. In one embodiment, a program code is instrumented that creates trace data supplier to write performance trace data via CPT API 152-156 to database 120. Trace model 110 that is in communication with Mbean server 108 and database 120 allows accessing of trace data at database 120 via UI 106 by providing a merged trace data received from multiple monitored systems 122, 136, 146 via corresponding trace data importers 114-118 located at central data provisioning 112. Trace model 110 also provides for filtering and aggregation of trace data. To allow for proper access and analysis of trace data originating from multiple sources 112, 136, 146, the trace data is converted into a common format or structure (e.g., CPT format, CPT structure, etc.) and provided to the user via client 102 further via UI 106.

Various modules and components are employed at monitored systems 122, 136, 146 to facilitate tracing and for collection, processing, and exporting of trace data. For example, J2EE monitored system 122 includes trace file storage 124 and server node 126, which includes trace data supplier 128, model provider 132, writer API 130, and Mbean server 134. In one embodiment, model provider 132 is implemented as MBean registered to the local system MBean server 134 and allows the accessing of trace data from CAS 104. Trace file storage 124 is referred to as a CPT file that serves as a temporary storage for trace data at monitored system 122. Trace data supplier 128 is a source of trace data, while write API provides a CPT API for trace data writing and serves as a CPT tracer.

ABAP monitored system 136 include a Computer Center Management System (CCMS) agent 144 that allows CCMS to access trace data for the local ABAP system 136. The trace data is provided to CCMS agent 144 via trace file provider 142 and stored at trace file storage 138 and received using work process 140. The trace data is retrieved from ABAP monitored system 136 and exported to CAS 104 by performing RFC calls to CCMS via CCMS agent 144. The trace data is imported at CAS 104 via ABAP CCMS importer 116 and then stored at database 120. In one embodiment, a number of systems can be monitored and trace data from such systems may be provided to CAS 104 so that it can then be converted into and provided as a common CPT structure trace data for access and analysis by client 102. For example, a third party monitored system 146 is illustrated that includes various third party compatible functional modules and components to collect trace data and provide it to CAS 104. Such modules may include a third party trace data writer 158, a third party agent 148, and a third party trace storage 150 to perform their respective functions as with modules and components at other monitored systems 122, 136. Further, a third party importer 118 at CAS 104 is employed to import trace data from the third party monitored system 146.

In one embodiment, CPT architecture 100 provides a CPT format and correlation. The CPT format is CIM-compliant and provides a common format to perform traces to (1) define the type of data that is needed to analyze performance and/or functional problems, (2) allow for common central storage of trace data at database 120, which provides a common mechanism for persistence, management, and analysis, and (3) provide for correlation. Correlation allows for grouping (e.g., correlating) of trace records that belong to a single logical transaction by introducing a correlation, which is an abstract object. CPT architecture 100 further provides for selective and centralized switch of tracing data for involved components and traces types and structures. In one embodiment, the CPT reports of trace data may be implemented using UI application framework 106, such as the WebDynpro framework. The trace data is stored at database 120 using trace model 110 implemented as Mbean and registered with Mbean server 108 of CAS 104. Trace model 110 provides trace data both as race trace records and aggregated data.

In one embodiment, a user activity triggers requests that are processed by various components at monitored systems 122, 136, 146 and CAS 104. For example, a web request from client 102 is sent to a J2EE application server associated with J2EE monitored system 136. Similarly a request may be sent to other system, such as ABAP system 136 and any other third party system 146. Components at various systems 122, 136, 146 produce different traces appropriate for analyzing several functional and performance problems. Abstract correlator objects are introduced to allow end-to-end analysis of applications and user activities that are processed by components running at various systems 122, 136, 146. Such correlator objects provide for combining performance and trace data from different origins, such as different system 122, 136, 146, (2) serializing the trace data over a network and transferring the trace data to CAS 104 via the metadata of various communication protocols, and (3) providing the trace data via a common structure to provide performance activities of applications, program codes, and user activities that are being monitored and analyzed.

FIG. 2A illustrates an embodiment of a common performance test application programming interface 204. In one embodiment, trace data 206-210 is collected from various trace data sources or providers (e.g., systems 122, 136, 146 of FIG. 1) and then provided to CPT database (e.g., database 120 of FIG. 1) at central administration system (e.g., CAS 104 of FIG. 1) via CPT API 204. CPT API may be associated with any number of modules and components, such as importers, writers, etc., to provide a way for trace data 206-210 to be provided at CPT database 202. CPT includes two development components: (1) a core library and (2) a service. The core library exposes CPT API 204 that allows instrumentation for writing performance traces by various components. The service is to configure CPT API 204 and view the gathered performance data.

CPT API 204 enables the currently existing functionalities in tracing (e.g., SQLTrace). Such functionalities include (1) reading trace data in an appropriate format for the corresponding application (e.g., OpenSQLMonitors application), (2) writing a trace record (together with metrics) is an atomic operation, (3) allowing the writing of trace data to a non database storage, and allowing the writing of trace data at server startup. Objects associated with CPT API 204 that are used for direct instrumentation of a trace data provider include (1) a factory object (e.g., CPTFactory) that is responsible for generating CPT provider objects via configuration, (2) a provider object (e.g., CPTProvider) which is used by the instrumented code to provide a lookup action and metric definition objects that are defined in the configuration thus identifying a single trace data provider, (3) a record object (e.g., CPTRecord) that is used as a main entity to be persisted via CPT API 204. Record objects contain performance information for measured action.

Each trace record that is received from various providers (e.g., monitored systems) is then configured to a common structure (e.g., CPT structure) and is stored at database 202. A CPT trace record may contain any number of metrics. Such metrics are valued from the instrumented code at data providers (e.g., monitored systems) and are assigned to the CPT trace record by calling a particular API method, such as an API addMetric( ) method. If necessary, an CPT trace record may be extended. CPT configuration may be separated in two parts: static configuration and dynamic (online) configuration. The two configurations may be regarded as two different use cases. A static configuration file may be part of CPT API 204 and used for such initialization of CPT API 204 so it can be directly used by the data providers by having the static configuration contain default CPT writer settings. Static configuration is also used to predefine certain objects, such as application layers, system layers, and database layers, etc. Also, the static configuration defines certain general metric definitions, such as elapsed time, central processing unit (CPU) time, and memory allocation that are relevant for various types of performance traces. A dynamic configuration file is part of the component that provides performance trace data. The dynamic configuration file may contain provider specific configurations, like actions and metric definitions.

In one embodiment, CPT API 204 is initialized by a J2EE engine service where the currently existing performance trace service is to be extended with various functionalities. The performance trace service provides various correlators, such as a measurement correlator that is regarded as the main correlator and is used to group up trace records belonging to a certain measurement or trace. The measurement correlator is referred to as the parent correlator to other correlators that are additionally provided. Another correlator includes a J2EE Engine runtime info correlator that contains information about the corresponding J2EE Engine user/session/application. The origin of CPT trace records is at a monitored system, such as at a node of a J2EE server associated with a J2EE system. To achieve a writing performance trace at server startup, a default correlator is employed for each virtual machine (VM). Default correlators may not contain any data relating to the monitored system. Further, for each trace data provider or monitored system, a default layer may be defined. The default layer is then automatically assigned to CPT trace records belonging to the corresponding trace data provider.

FIG. 2B illustrates an embodiment of a mechanism 250 for using a common performance test application programming interface. In one embodiment, CPT API is initialized 252 via a configuration file. The configuration file defines a provider that writes trace data in file storage. The configuration file further creates metric definitions of types, such as string, long, and double. CPT API is further initialized using a program code 254. CPT API allows the defining of a trace data provider using Extensible Markup Language (XML) configuration file or dynamically in the code. The CPT API initialization includes two types initializations: a static API initialization 256 and a dynamic API initialization 258. Various modules, components, and actions are defined dynamically defined 260 using a program code. An action may be for creating a CPT trace record. Then, a CPT trace record is written 262.

FIG. 3 illustrates an embodiment of a common performance trace architecture 300 having a central administration system 304. In one embodiment, CAS 304 is coupled to client 302 and systems that are being monitored for and are providers of trace data, such as J2EE monitored system 334 and ABAP monitored system 336. J2EE and ABAP system 334, 336 are coupled with CAS 304 via trace manager 310 that resides at CAS 304. Trace manager 310 is used to perform collection and analysis of trace data. Trace manager 310 is coupled to a UI 306 via Java Management Extensions (JMX) interfaces. Client 302 accesses trace information at trace manager 310 via a display application exposed via UI 306. For example, various XML files may be downloaded from client 302.

In one embodiment, trace data from J2EE and ABAP systems 334, 336 is imported at CAS 304 via various module and components, such as a CPT API and importers (e.g., CPT importer 312, import module 318, etc.). CPT importer 312 is used to import data from J2EE monitored system 334 and place it at database 322. The files having the trace data are first saved at file system 324 before being imported into database 322. Import module 318 may be used to import trace data from ABAP monitored system 336 and from any other system (such as the third party monitored system 146 of FIG. 1) and place it at database 322. For each ABAP trace, a reader class may be generated to be used to form an importer API of the CPT library. ABAP system 336 is in communication with trace manager 310 via RFC connector API 330. RFC connector API 330 serves as a proxy of RFC function modules and creates a general framework for connection to ABAP system 336. In addition to having and communicating with an ABAP system 336, a CCMS system 332 may also be added to CAS 304.

CAS 304 further includes configuration module 316 that contains methods for starting and stopping various trace activities, and for keeping general information (e.g., name, start data, end data, filters, etc.) about such activities. Configuration module 316 is in communication with configuration storage 328 where configuration data is stored. When a HyerText Transfer Protocol (HTTP) proxy is used on the client side, several XML files are generated as a result of that. These files are then uploaded to CAS 304 and with the help of a file (e.g., responses.trc file) that is generated by an HTTP service. Such HTTP analysis are generated and imported to CAS 304 via HTTP analysis module 320. Once trace activities are stopped and trace data form such activities are collected from monitored systems 334, 336 and imported into database 322, the trace data may then be kept at analysis storage 326 and analyzed by analysis module 314.

FIG. 4 illustrates an embodiment of a process for tracing and importing trace data. At processing block 402, a trace activity is started such that program codes or applications at a system (e.g., J2EE system, ABAP system, etc.) can be monitored for trace data. It is contemplated that multiple trace activities may be started at multiple corresponding systems. In one embodiment, a user (e.g., administrator, developer, etc.) may select to start or generate the trace activity using system selection via a Web administration UI. For example, a Uniform Resource Locator (URL) is selected by the user at an Internet browser (e.g., Microsoft Explorer®, Netscape Navigator®) at a system. The user triggers the trace activity which then starts at a corresponding monitored system. At decision block 404, whether the trace activity is to be stopped is determined. If the trace activity is to be stopped, it is stopped at processing block 404 and the process ends at termination block 414. This can be triggered by the user via the UI. In case of multiple trace activities, the user may select to stop one or more trace activities, but not all of them. For example, the user my select to end the trace activity at a J2EE system, but continue with the ABAP and other systems. If the trace activity is not to be stopped, it continues with decision block 406.

At decision block 406, a determination is made as to whether the trace activity is to be deleted. If for any reason (e.g., incorrect application being traced, tracing data is correct, etc.), the trace activity at any given system is to be deleted at processing block 408, it is deleted and the process ends at termination block 414. This is can be accomplished by the user via the UI. In case of multiple trace activities, it is contemplated that one or more trace activities may be deleted, while still performing one or more other trace activities. If the trace activity is not to be deleted, the processing continues with collecting of trace data at the monitored system at processing block 410. When multiple trace activities are performed at multiple monitored systems, the trace data collected from each of those monitored systems may be of format and structure. For example, J2EE traces may be different in structure from ABAP traces. At processing block 412, the trace data is imported to a central database that provides a common structure of all trace data. The trace data having different structures is imported and converted into a common structure for the user to access and analyze at the central CPT database. This import may be performed via a number of CPT APIs, importers, import modules, temporary storages, and other modules and components. The process ends at processing block 414.

FIG. 5 illustrates an embodiment of a trace data structure 500 represented at a common performance trace database. In one embodiment, a CPT API is used to store and manipulate trace data, including converting trace data of various formats and structures obtained from various monitored system into a common format/structure to be provided via a central CPT database. Once the import and conversion of trace data is performed from various systems to the CAS, the trace data is stored at the CPT database and represented in a special way such that the trace data is easily retrieved and manipulated. In one embodiment, the CPT mechanism uses two types of storage systems. The first type of storage system includes a file storage that is used to store CPT trace during execution of certain functionalities (e.g., to record processes in execution, etc.). The other type of storage system includes a database storage (e.g., central CPT database) that is capable of being used for manipulating trace data (e.g., to retrieve specific records, to retrieve records with specified correlation or specified provider, etc.).

In the illustrated embodiment, the database storage of trace data is shown as having various modules, records, etc. For example, a CPT-compatible trace data format or structure contains a stream of six files, such as (1) file origins, (2) file metrics, (3) file correlators, (4) file metadata, (5) file record correlator, and (6) file records. Each of the elements 502-520 illustrated here are contained in one or more such streams of files. For example, CPT metric definition 502, which contains unique identification, may be contained in file metrics, but repeated in file origins. CPT origin 520 includes a node from where a record (e.g., CPT record 512) originates. CPT origin is found in file metadata and when combined with the unique identification from CPT metric definition 502 provides a global identification for the record 512. CPT module 508 provides the name of the logical unit (e.g., class name) corresponding to the record originated. CPT module 508 is contained in file metadata. CPT action 506, which is in communication with CPT module 508, provides the name (e.g., method name) of a module subsection which measures execution time.

CPT thread 522 provides a unique identification of the thread executing the module. CPT thread 522 is located in file metadata. CPT provider 514 is a provider of the record 512 and is contained in file metadata. Examples of trace data handled by a CPT provider 514 include SATrace, SQLTrace, APPTrace, etc. The providers, for example, may include SATrace, SQLTrace, APPTrace, etc. Based on the provider name, the visualizer can use plug-ins for additional processing. CPT record 512 includes the record that is originated, provided, and used and is associated with other elements 502-510, 514-522. CPT record 512 resides in file records. CPT record 512 may also include a parent identification which may be used when there is a nesting of trace records and may contain the identification of the parent record.

CPT metric 504 is located at file metrics. CPT metric 504 represents metrics having a set of (name=value) pairs giving additional information about a call. For example, CPT metric can describe a method call parameters, or in case of a database call, some database related values may be provided. These properties can be parsed by the visualizer to a provider specific plug-in or merely can be used as a more detailed description of the record 512. Trace data structure 100 further includes correlators, such as CPT record correlator 510 that resides at file record correlator, CPT correlator 516 that resides at file origins, and CPT correlator definition 518 that resides at file metadata. These correlators 510, 516, 518 provide a value that defines and provides to which measurement or trace the record 512 belongs. For each measurement, a separate correlator 510, 512, 512 may be defined.

FIG. 6 illustrates an embodiment of a process for tracing at multiple systems and providing access to trace data. In one embodiment, at processing block 602, tracing at multiple systems (e.g., J2EE system, ABAP system, etc.) is started. Tracing can be started by having a Web administration application (e.g., Web Dynpro application) run as triggered by a user via a client via a UI. Once tracing has started, tracing data from various monitored systems is collected at processing block 604. At decision block 606, whether any unusual or non-compatible trace data is being collected is determined. If there is such trace data (e.g., trace data that is not CPT compatible, flawed data, etc.), that trace data is fixed at processing block 608. Examples of the fixing of such trace data includes deleting any flawed data, stopping the tracing at one or more systems, converting the trace data that is not compatible with CPT into trace that is compatible with CPT, etc.

Once the non-compatible or unusual data is fixed or if not such trace data is found, the trace data collected is then imported from multiple systems at a database that is central to a central administration system that is compatible with CPT at processing block 610. As it is discussed elsewhere in this document, compatible trace data may be imported directed so the database via a CPT API, while the importing of other trace data (e.g., non-compatible data) may include the use of additional modules and components, such as an import module, a trace data conversion module, etc. Such trace data is then merged and stored at the database at processing block 612. At processing block 614, access to the trace data stored at the database is provided to the user via the client and the UI.

FIG. 7A illustrates an embodiment of a common performance trace architecture 700 having a central administration system 702. In one embodiment, CPT architecture 700 employs an end-to-end (E2E) tracing technique to analyze the performance of a request to the host server having J2EE engine 704 and ABAP engine 706 that are being monitored for tracing. For example, a user can place a request to pen an E2E application at CAS 702. This creates a trace activity, which means the engines 704, 706 are turned on in trace mode. The user may then enter a URL to perform actions leading to the request. The user may then choose to stop the trace activity and any trace data resulting from the activity. The trace data may then be imported from the monitored J2EE and ABAP systems 704, 706 to a database at CAS 702.

In one embodiment, the trace data may then be provided via a common format (e.g., CPT format) for the user to access, view, and analyze via a client. For example, the user may view an overview of a selected system 704, 706 and the times and percentages used for tracing as associated with the selected system 704, 706. Also, the user can view database records associated with systems 704, 706. Further, the user can have the trace data displayed as functions calls for any of the selected systems 704, 706 in a tree or graph representation and further view a display of aggregated numbers of such function calls.

FIG. 7B illustrates an embodiment of a central administration system 702. For brevity, components described elsewhere in the document are not discussed here. In one embodiment, for generating and providing function call analysis, a CPT database 720 is used to hold trace data or records in a common format (e.g., CPT format). Database manager 716 serves as a reader of such trace records stored at database 720. Analysis model 712 includes a module that is used to prepare the trace records that are then to be displayed via graphs to the user. A UI 708 may be employed to help display the trace data via graphs and other formats to the user. In one embodiment, analysis model 712 analyzes the trace data read by database manager 716 and may further include or be associated with a graph generation module to generate graph to represent functions calls and related data. Such graphs are illustrated in FIGS. 8A-8B and 9A-9B. Functions calls are represented in various ways in database 720. Examples of function call representation are as follows:

Start ID Function Call Name Time Duration ParentID 0 NW.J2E:SRV:HTTP 9380 −1 1 NW:J2E:SRV:WEB_REQUEST 9379 1

In one embodiment, trace data is provided to the client via, for example, an HTTP analyzer for evaluating the end user experience while working with an application. For example, the following metrics may be provided for the user to evaluate and analyze the trace data: information about the requests associated with a user click, and an overall duration of the user click. For each request is provided: a URL, an overall duration, time spent in client-side rendering of trace data, time spent in network communication, and time lag of the beginning of the user request calculated on the base of the user trace start event. Further, to allow further correlations between the client-side trace data and the sever side traces, the trace data for requests are bound to a single correlation identification (correlation ID), which may be part of the passport. An exemplary result using an HTTP analyzer is provided in FIG. 9B.

To display Java or J2EE SQL trace data via central UI 708, for a drill-down process, filter by passport GUID and filter by time period are provided. The displaying or viewing of the Java SQL trace data is similar to how an open SQL monitor application is implemented. Further, a list of open SQL records is provided for each records, the list includes: timestamp, duration; runtime information about the user, application, and session; invoked Java Database Connectivity (JDBC) method and result; SQL statement, aggregation of repeating JDBC next( ) calls; and connection executing the JDBC operation.

To display SQL trace data, the same SQL trace analysis may be used for both the J2EE/Java and ABPA trace to be provided via central UI 708 to the client. To display any ABAP Remote Function Call (RFC) trace data via central UI 708, filter by passport Globally Unique Identifier (GUID) and filter by time period may be used for a drill down. Also, to display and view ABAP RFC records provided by ST05 transactions, following metrics may be provided for each record: timestamp; function module name; ABAP program name; duration; and transferred input/output (I/O). To display ABAP statistical records via central UI 708, filter by passport GUID and filter by time period may be used for a drilldown. To display and view ABPA SR, the following displayed record attributes may be used: timestamp, server, transaction, program, user, response time, wait time, CPU time, database time, load and general memory, and transferred I/O.

In one embodiment, central configuration UI 708 the is part of the UI allows for enabling/disabling of trace modes of J2EE engine 704, and keeps information about various trace activities. To start a trace activity, the user may supply some information, such as name to provide the user name for a trace session, and trace level (e.g., low, medium, high, etc.). Further, in addition to choosing these levels, types of trace providers maybe chosen, such as HTTP analysis, IS transaction trace, J2EE SQL trace, ABAP SQL trace, ABAP RFC trace, and ABAP trace (e.g., SE30) etc. A trace can be triggered by, for example, URL parameters, activity overview reports.

Central UI 708 may provide an entry point view for analysis and process that result in narrowing the time period (e.g., time-based drill-down). The end point of trace analysis provides for a display or view of traces, such as SQL trace and RFC trace. The correlation between the traces may be based on a passport GUID. For each trace views, filtering by passport GUID and time period are allowed. The processes may include an entry (e.g., HTTP analyzer), and a narrow to specific request that entered J2EE engine, which includes narrow to strong component or method as defined in the transaction tracer, and jump to specific view for functional analysis to one of the following traces in J2EE engine 704 (e.g., SQL trace). If the component corresponds to a request to an ABAP backend system, the process jumps to the corresponding trace views for performance and function analysis in ABAP system 706, such as requests, SQL trace, RFC trace, and statistical records.

FIGS. 8A-8B illustrate embodiments of chart representation graphs 800, 850 of function calls. FIG. 8A illustrates represents a screenshot showing a chart representation graph 800 representing function calls 804-816 relating to trace data. The first line from the bottom representing function call 816 is also the root call of all function calls, while function calls 804-814 are nested calls of the function one level below. This chart representation graph 800 is different from a tree representation graph in which the root call is not obvious or clearly marked. Further, each function call 804-816 here in chart representation graph 800 is represented in a single line, the length of which shows the time 820 (e.g., in milliseconds (ms)) it took for the corresponding call to be executed and the depth 818 of which represents the number of calls 802 involved in a particular process of tracing. Also, unlike in a tree representation graph, this graph 800 illustrates the longest call 816 and the following nested invocations, such as call 814, call 812, call 810 and so forth. Further, different color may be assigned to various calls to further illustrate the length, time, importance, etc. of the calls.

FIG. 8B illustrates an embodiment of a chart representation graph 850 to further explain graph 800. As illustrated, the x-axis illustrates time 854 (e.g., shown in seconds (s) here for clarity) it takes for a call to be processed and the y-axis illustrates the number of calls or components 852 called or involved in the process. For example, call is the root call and also the longest call, but the longest stretch of a call is 864 which runs for over two seconds (e.g., 8.5s-11s), while the shortest stretch is 862 which runs for about half a second (e.g., 7s-7.5s). Similarly, the deepest call is 860 that involves four calls (calls 1-4), while there are not so deep calls involving a single call. The illustrated process begins at point 856.

FIGS. 9A-9B illustrate embodiments of chart representation graphs 900, 950 of data aggregates of function calls. As illustrated in FIG. 9A, the x-axis represents aggregated time 918 (e.g., in ms), while the y-axis represents calls of components 902. Time 918 may represent the total or aggregated time for each call or component 904-916 in action and may also represent and provide the exact call execution time at every stage and even other information, such as who calls who. Referring now to FIG. 9B, it represents a chart graph 950 to represent data aggregation of function calls and further explain graph 900 of FIG. 9A. As illustrated, the x-axis represents aggregated time 966 for each function call or component 954-964 that is shown on y-axis. For example, call 954 is shown to have the longest aggregated time, while call 956 is shown to have the shorted aggregated time. These results are obtained when using an HTTP analyzer. Also, colors may be assigned to calls or components 952 to further illustrated the exact duration of each call 954-964 at each stage of the process. For example, color-coding may represent pre-processing time, network time, server time, rendering time, etc.

FIG. 10 illustrates an embodiment of a process for creating and displaying trace data. At processing block 1002, a trace activity is created. This can be accomplished by having a user place a request with a remote system (e.g., J2EE system, ABAP system, etc.) via a central administration system and UI provided via the CAS. At processing block 1004, the tracing activity commences, which includes tracing of one or more applications at one or more remote systems that are being monitored. At processing block 1006, the trace activity is stopped. It can be done by having the user stop the on-going trace activity. At processing block 1008, trace data from the remote monitored systems is imported at a database provided by the CAS via a common format interface (e.g., CPT API). This trace data is then displayed to the user, for example, in response to a request from the user at processing block 1010. The data may be displayed in a tree-like or chart-like graph format. The chart-like graph may further provide data aggregation of functions calls and components associated with the trace data.

FIG. 11 illustrates an embodiment of a process for importing and displaying trace data. At processing block 1102, trace data is imported from one or more remote systems (e.g., J2EE system, ABAP system, etc.) to a database at a central administration system. At processing block 1104, the trace data is read by a database manager at the CAS for detecting various components, factors, functions calls (collectively referred to as “calls”), etc. Such calls are tracked, particularly during execution, at processing block 1106. Any data relating to such calls is determined and collected at processing block 1108. The detailed representation of such data relating to the calls is displayed via various graph formats, such as a chart-like graph, a tree-like graph, etc. at processing block 1110. Examples of chart-like graphs are illustrated in FIGS. 8A-8B. Further, an aggregated representation of these calls may be displayed via a chart-like graph providing aggregated results of the data at processing block 1112. Examples of chart-like graphs representing aggregated data results are illustrated in FIGS. 9A-9B.

In one embodiment, to perform various embodiments of the present invention, a server or node (e.g., J2EE server) is employed, which supports Enterprise Java Bean (EJB) components and EJB containers (at the business layer) and Servlets and Java Server Pages (JSP) (at the presentation layer). A virtual machine (VM), including a Java virtual machine (JVM), may be employed to host the server or server node. It is understood that processes taught by the discussion above can be practiced within various software environments such as, for example, object-oriented and non-object-oriented programming environments, Java based environments (such as a J2EE environment or environments defined by other releases of the Java standard), other environments (e.g., a .NET environment, a Windows/NT environment each provided by Microsoft Corporation), and the like.

Processes taught by the discussion above may be performed with program code, such as machine-executable instructions, which can cause a machine (such as a “virtual machine”, a general-purpose processor disposed on a semiconductor chip, a special-purpose processor disposed on a semiconductor chip, etc.) to perform certain functions. Alternatively, these functions may be performed by specific hardware components that contain hardwired logic for performing the functions, or by any combination of programmed computer components and custom hardware components.

One or more modules within or associated with an enhanced configuration architecture (such as common performance trace architecture 100 of FIG. 1) and its sub-architectures and systems (e.g., central administration system 104), APIs (e.g., CPT API), and its modules, models, components, and other elements may include hardware, software, and a combination thereof. In a case where a module includes software, the software data, instructions, and/or configuration may be provided via an article of manufacture by a machine/electronic device/hardware. An article of manufacture may include a machine accessible/readable medium having content to provide instructions, data, etc. The content may result in an electronic device, for example, a filer, a disk, or a disk controller as described herein, performing various operations or executions described. A machine accessible medium includes any mechanism that provides (i.e., stores and/or transmits) information/content in a form accessible by a machine (e.g., computing device, electronic device, electronic system/subsystem, etc.). For example, a machine accessible medium includes recordable/non-recordable media (e.g., read only memory (ROM), random access memory (RAM), magnetic disk storage media, optical storage media, flash memory devices, etc.), as well as electrical, optical, acoustical or other form of propagated signals (e.g., carrier waves, infrared signals, digital signals, etc.), etc. The machine accessible medium may further include an electronic device having code loaded on a storage that may be executed when the electronic device is in operation. Thus, delivering an electronic device with such code may be understood as providing the article of manufacture with such content described above. Furthermore, storing code on a database or other memory location and offering the code for download over a communication medium via a propagated signal may be understood as providing the article of manufacture with such content described above. The code may also be downloaded from a remote computer (e.g., a server) to a requesting computer (e.g., a client) by way of data signals embodied in a propagation medium (e.g., via a communication link (e.g., a network connection)).

FIG. 12 illustrates a computing system 1200. Computing system 1200 may be used for implementing one or more embodiments of the present invention and for executing program code stored by an article of manufacture. It is important to recognize that the computing system 1200 represents merely of various computing system architectures that can be used for the same purposes. The applicable article of manufacture may include one or more fixed components (such as hard disk drive 1202 or memory 1206) and/or various movable components, such as compact disk (CD) ROM 1204, a compact disc, a magnetic tape, and the like. To execute the program code, typically instructions of the program code are loaded into RAM 1206. Then, processing core 1208 executes the instructions. A processing core may include one or more processors and a memory controller function. A virtual machine or “interpreter” (e.g., a JVM) may run on top of the processing core (architecturally speaking) to convert abstract code (e.g., Java bytecode) into instructions that are understandable to the specific processor(s) of processing core 1208. Computing system 1200 further includes network interface 1210 and bus 1212 to connect to other systems via a network and to have various components communicate with each other, respectively.

FIG. 13 illustrates a client/server network system 1300. As illustrated, network 1308 links server 1310 with client systems 1302-1306. Server 1310 includes programming data processing system suitable for implementing apparatus, programs, and/or methods in accordance with one or more embodiments of the present invention. Server 1310 includes processor 1312 and memory 1314. Server 1310 provides a core operating environment for one or more runtime systems (e.g., VM 1316) at memory 1314 to process user requests. Memory 1314 may include a shared memory area that is accessible by multiple operating system processes executing in server 1310. For example, VM 1316 may include an enterprise server (e.g., a J2EE-compatible server or node, Web Application Server developed by SAP AG, WebSphere Application Server developed by IBM Corp. of Armonk, N.Y., and the like). Memory 1314 can be used to store an operating system, a Transmission Control Protocol/Internet Protocol (TCP/IP) stack for communicating over network 1308, and machine executable instructions executed by processor 1312. In some embodiments, server 1310 may include multiple processors, each of which can be used to execute machine executable instructions.

Client systems 1302-1306 may execute multiple application or application interfaces. Each instance or application or application interface may constitute a user session. Each user session may generate one or more requests to be processed by server 1310. The requests may include instructions or code to be executed on a runtime system, such as VM 1316, on server 1310 and its components and modules as described throughout this document.

In addition to what is described herein, various modifications may be made to the disclosed embodiments and implementations of the invention without departing from their scope. Therefore, the illustrations and examples herein should be construed in an illustrative, and not a restrictive sense. The scope of the invention should be measured solely by reference to the claims that follow. 

1. A method comprising: importing trace data at a database from a provider; tracking a plurality of factors associated with the trace data; and generating a first graph to represent each of the plurality of factors associated with the trace data.
 2. The method of claim 1, further comprising: reading the trace data to determine the plurality of factors; analyzing the plurality of factors prior to generating the first graph; and collecting analysis data relating to each of the plurality of factors.
 3. The method of claim 2, further comprising representing the analysis data relating to the plurality of factors via the first graph.
 4. The method of claim 3, wherein the first graph comprises a plurality of bars, wherein each bar represents a factor of the plurality of factors.
 5. The method of claim 2, further comprising: aggregating the analysis data for each factor of the plurality of factors; and generating a second graph to represent the aggregated analysis data.
 6. The method of claim 1, further comprising providing access to a client system to the first graph and the second graph stored via a user interface.
 7. The method of claim 6, further comprising displaying the first graph and the second graph at the client system via a display device.
 8. The method of claim 1, wherein the provider comprises one or more of a Java 2 Enterprise Edition (J2EE) system and an Advanced Business Application Programming (ABAP) system.
 9. The method of clam 1, wherein the database resides at a trace data administration system to provide the trace data via a common format, the common format including a common performance trace (CPT) format that is in compliance with a common interface model (CIM).
 10. A system comprising: a client system to initiate a trace activity at a provider; and a server system coupled with the client system, the server system having a trace data administration system, the trace data administration system to import trace data at a database from the provider, the trace data resulting from the trace activity initiated by the client system, track a plurality of factors associated with the trace data, and generate a first graph to represent each of the plurality of factors associated with the trace data.
 11. The system of claim 10, wherein the trace data administration system is further to: read the trace data to determine the plurality of factors; analyze the plurality of factors prior to generating the first graph; and collect analysis data relating to each of the plurality of factors.
 12. The system of claim 11, wherein the trace data administration system is further to represent the analysis data relating to the plurality of factors via the first graph
 13. The system of claim 12, wherein the first graph comprises a plurality of bars, wherein each bar represents a factor of the plurality of factors.
 14. The system of claim 11, wherein the trace data administration system if further to: aggregate the analysis data for each factor of the plurality of factors; and generate a second graph to represent the aggregated analysis data.
 15. The system of claim 10, wherein the trace data administration system is further to provide access to the client system to the first graph and the second graph stored via a user interface.
 16. An article of manufacture comprising a machine-accessible medium having instructions which when executed cause a machine to: import trace data at a database from a provider; track a plurality of factors associated with the trace data; and generate a first graph to represent each of the plurality of factors associated with the trace data.
 17. The article of manufacture of claim 16, wherein the instructions which when executed further cause the machine to: read the trace data to determine the plurality of factors; analyze the plurality of factors prior to generating the first graph; and collect analysis data relating to each of the plurality of factors.
 18. The article of manufacture of claim 17, wherein the instructions which when executed further cause the machine to represent the analysis data relating to the plurality of factors via the first graph.
 19. The article of manufacture of claim 18, wherein the first graph comprises a plurality of bars, wherein each bar represents a factor of the plurality of factors.
 20. The article of manufacture of claim 17, wherein the instructions which when executed further cause the machine to: aggregate the analysis data for each factor of the plurality of factors; and generate a second graph to represent the aggregated analysis data. 